Book Image

Hands-On Concurrency with Rust

By : Brian L. Troutwine
Book Image

Hands-On Concurrency with Rust

By: Brian L. Troutwine

Overview of this book

Most programming languages can really complicate things, especially with regard to unsafe memory access. The burden on you, the programmer, lies across two domains: understanding the modern machine and your language's pain-points. This book will teach you to how to manage program performance on modern machines and build fast, memory-safe, and concurrent software in Rust. It starts with the fundamentals of Rust and discusses machine architecture concepts. You will be taken through ways to measure and improve the performance of Rust code systematically and how to write collections with confidence. You will learn about the Sync and Send traits applied to threads, and coordinate thread execution with locks, atomic primitives, data-parallelism, and more. The book will show you how to efficiently embed Rust in C++ code and explore the functionalities of various crates for multithreaded applications. It explores implementations in depth. You will know how a mutex works and build several yourself. You will master radically different approaches that exist in the ecosystem for structuring and managing high-scale systems. By the end of the book, you will feel comfortable with designing safe, consistent, parallel, and high-performance applications in Rust.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Packt Upsell


In this chapter, we set the lower-level details of concurrency in Rust as a foundation. We discussed thread pools, which, it turns out, we had all the pieces in-hand from previous chapters, to understand a fairly sophisticated one. Then we looked into rayon and discovered that we could also understand an extremely sophisticated threadpool, hidden behind the type system to enable data parallelism in the programming model. We discussed architectural concerns with the thread-per-connection model and the challenges of splitting small datasets up into data parallel iterators. Finally, we did a walkthrough of a rayon and multi-processing-based genetics algorithm project. The std::process interface is lean compared to that exposed by some operating systems, but well-thought-out and quite useful, as demonstrated in the feruscore project that closed out the chapter. We'll pick up feruscore in the next chapter when we integrate C code into it, in lieu of calling out to a process.